Rapid advances in computing and networking technologies in the last decade have made it easier than ever create, store, distribute and consume huge amounts of information. This information includes not only sensitive personal data such as financial, medical and biometric information, but also private behavioural patterns monitored by social networking sites and surveillance video cameras. The unprecedented ease of accessing and distributing information has raised security and privacy concerns.
In response to this emphasis on security and privacy, there has recently been a surge of interest in research on privacy-preserving multiparty computation. This has been fuelled by practitioners at the interface of cryptography, signal processing, data mining and machine learning. Secure signal processing techniques have recently been proposed for biometric access control, data classification, electronic voting, recommender systems and Smart Grid privacy.
Our aim with this special issue is to highlight enabling technologies in privacy-preserving multiparty computation and to draw the attention of the community to this fertile area of truly interdisciplinary research. We would like to provide a view of what is possible with current mathematical primitives, as well as illuminate key unsolved issues in the field.
We seek submissions on all aspects of secure multiparty computation; topics of interest include but are not limited to:
- Secure multiparty computation primitives, homomorphic functions, secret sharing
- Privacy-preserving signal processing, sufficient statistics, probabilistic inference
- Problems and protocols for privacy preservation in the smart grid
- Privacy-preserving data mining for health care, finance, cloud computing
- Biometric cryptosystems and related secure authentication schemes
- Privacy-preserving multimedia surveillance
- Complexity analysis of privacy-preserving algorithms
Manuscript submission: 1 June, 2011
Notification of acceptance: 1 September, 2011
Revised final manuscript submission: 1 October, 2011